Design and simulation of adaptive speed control for SMO-based sensorless PMSM drive

The work presents an adaptive PI controller for sensorless permanent synchronous motor (PMSM) drive system. A rotor flux position of PMSM is estimated by using a sliding mode observer (SMO), firstly. The estimated rotor position will send to the current loop for current vector control and simultaneously feedback to the speed loop for speed control. Then to increase the performance of the PMSM drive system, a PI controller which its parameters are tuned by a radial basis function neural network (RBF NN) is applied to the speed controller for coping with the effect of the system dynamic uncertainty. In realization, the Very high speed IC Hardware Description Language (VHDL) is adopted to describe the behavior of the sensorless speed control IP (Intellectual Property) which includes the circuits of space vector pulse width modulation (SVPWM), vector control, coordinate transformation, SMO, PI controller, RBF NN, etc. Further, a simulation work is performed by MATLAB/Simulink and ModelSim co-simulation mode, provided by Electronic Design Automation (EDA) Simulator Link. The PMSM, inverter and speed command are performed in Simulink as well as the sensorless speed control IP is executed in ModelSim. Finally, some co-simulation results validate the effectiveness of the proposed sensorless PMSM IP.